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Applied Intuition

Technical Artist

February 2023 – June 2024

I joined Applied Intuition as a Technical Artist in February 2023, developing simulation and visualization tools for autonomous vehicle development. I worked at the intersection of real-time graphics, engineering, and product design to build systems that help AV engineers create and test virtual environments.

Material Editing System

2023 – 2024

Designed and built a full-stack material editing system inside Applied Intuition's sensor simulation product, allowing AV engineers to programmatically customize road surfaces, markings, and material properties in virtual environments. The system gives sensor manufacturers and software teams the ability to quickly generate varied synthetic training data and test specific reflectance values without manual 3D editing.

I owned the project end-to-end: designing the API, building the Unreal Engine backend, and — after the PM requested a frontend — learning React in four weeks to ship a GUI that lets users browse material presets and fine-tune parameters in-product.

Material editing GUI — users can browse presets and fine-tune parameters in real time

Surface material variants applied to a parking lot environment

Realistic material editing — adjusting reflectance and surface properties

Unreal Engine C++ HLSL React YAML Sensor Simulation

Contributions

API design — Designed a future-proof, extendable API that lets users select objects, choose material presets, and fine-tune parameters without locking into specific engine internals
Unreal backend — Implemented the material editing pipeline in C++, connecting user-facing controls to Unreal's material system and shaders
React frontend — Learned React in four weeks and partnered with frontend engineering to build a GUI leveraging the product's YAML-to-GUI feature, significantly improving usability
XFN collaboration — Gathered input from users, TAs, engineers, and designers to find the right balance between flexibility and guard rails

Custom Streetlights

2023 – 2024

Built a system that allows users to programmatically customize streetlights in parking lot simulation scenes. The project was driven by a customer need: nighttime environments with minimal lighting are a known challenge for autonomous vehicle perception systems, and teams needed a way to reliably generate and control those conditions at scale.

The streetlight system gives users direct control over placement, intensity, color temperature, and coverage, enabling repeatable nighttime test scenarios for sensor validation and AV software training.

Streetlight customization system — programmatic control over placement and lighting parameters

Nighttime parking lot with rain — a challenging scenario for autonomous perception systems

Unreal Engine C++ HLSL Sensor Simulation Lighting

Contributions

Programmatic lighting control — Built a system for scripting streetlight properties (placement, intensity, color temperature, spread) across scenes without manual in-editor editing
Nighttime scenario support — Enabled customers to generate repeatable low-light test conditions that are critical for validating AV perception in challenging environments
Unreal content pipeline — Developed C++ tooling to maintain performance and visual quality standards for real-world simulation fidelity